import gradio as gr
from PIL import Image
from inference import get_pipeline

def tryon(person_img, cloth_img):
    pipeline = get_pipeline()
    result, meta = pipeline.run_inference(person_img, cloth_img, num_steps=25)
    return result, f"Seed: {meta['seed']} | Time: {meta['timings']['total_ms']} ms"

demo = gr.Interface(
    fn=tryon,
    inputs=[gr.Image(type="pil", label="Person"), gr.Image(type="pil", label="Garment")],
    outputs=[gr.Image(type="pil", label="Result"), gr.Textbox(label="Metadata")],
    title="CatVTON Virtual Try-On",
    description="Upload a person image and a garment image to visualize the CatVTON try-on result.",
    allow_flagging="never",
)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)